a b s t r a c tFrom June 2005 to March 2007, we investigated wolf presence in an area of 1000 km 2 in central northern Portugal by scat surveys along line transects. We aimed at predicting wolf presence by developing a habitat model using land cover classes, livestock density and human influence (e.g. population and road density). We confirmed the presence of three wolf packs by kernel density distribution analysis of scat location data and detected their rendezvous sites by howling simulations. Wolf habitats were characterized by lower human presence and higher densities of livestock. The model, developed by binary logistic regression, included the variables livestock and road density and correctly predicted 90.7% of areas with wolf presence. Wolves avoided the closer surroundings of villages and roads, as well as the general proximity to major roads. Our results show that the availability of prey (here: livestock) is the most important factor for wolf presence and that wolves can coexist with humans even in areas of poor land cover, unless these areas are excessively fragmented by anthropogenic infrastructures.

Despite severe population declines and an overall range contraction, some populations of large carnivores have managed to survive in human-modified landscapes. From a conservation perspective, it is important to identify the factors allowing for this coexistence, including the relevant habitat characteristics associated with the presence of large carnivores. We evaluated the role of several environmental factors describing habitat quality for wolves Canis lupus in the humanised Iberian Peninsula, which currently holds an important wolf population at European level. We used maximum entropy and generalized linear model approaches in a nestedscale design to identify the environmental factors that are related to wolf presence at three spatial scales and resolutions: (1) distribution range: wolf presence on a 10 9 10 km grid resolution, (2) wolf habitat use: wolf occurrence on a 2 9 2 km grid and (3) dens/rendezvous sites: breeding locations on a 1 9 1 km grid. Refuge availability, as defined by topography, seemed to be the key factor determining wolf presence at the multiple scales analysed. As a result, wolf populations may coexist with humans in modified landscapes when the topography is complex. We found that a significant amount of favourable habitat is not currently occupied, suggesting that the availability of suitable habitat is not the limiting factor for wolves in the Iberian Peninsula. Habitat suitability outside the current range indicates that other factors, such as direct persecution and other sources of anthropogenic mortality, may be hampering its expansion. We suggest that priorities for conservation should follow two general lines: (1) protect good quality habitat within the current range; and (2) allow dispersal to unoccupied areas of good quality habitat by reducing human-induced mortality rates. Finally, we still need to improve our understanding of how wolves coexist with humans in modified landscapes at fine spatiotemporal scales, including its relationship with infrastructures, land uses and direct human presence.

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Mammals are threatened worldwide, with ~26% of all species being included in the IUCN threatened categories. This overall pattern is primarily associated with habitat loss or degradation, and human persecution for terrestrial mammals, and pollution, open net fishing, climate change, and prey depletion for marine mammals. Mammals play a key role in maintaining ecosystems functionality and resilience, and therefore information on their distribution is crucial to delineate and support conservation actions. MAMMALS IN PORTUGAL is a publicly available data set compiling unpublished georeferenced occurrence records of 92 terrestrial, volant, and marine mammals in mainland Portugal and archipelagos of the Azores and Madeira that includes 105,026 data entries between 1873 and 2021 (72% of the data occurring in 2000 and 2021). The methods used to collect the data were: live observations/captures (43%), sign surveys (35%), camera trapping (16%), bioacoustics surveys (4%) and radiotracking, and inquiries that represent less than 1% of the records. The data set includes 13 types of records: (1) burrows | soil mounds | tunnel, (2) capture, (3) colony, (4) dead animal | hair | skulls | jaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8), observation in shelters, (9) photo trapping | video, (10) predators diet | pellets | pine cones/nuts, (11) scat | track | ditch, (12) telemetry and (13) vocalization | echolocation. The spatial uncertainty of most records ranges between 0 and 100 m (76%). Rodentia (n =31,573) has the highest number of records followed by Chiroptera (n = 18,857), Carnivora (n = 18,594), Lagomorpha (n = 17,496), Cetartiodactyla (n = 11,568) and Eulipotyphla (n = 7008). The data set includes records of species classified by the IUCN as threatened (e.g., Oryctolagus cuniculus [n = 12,159], Monachus monachus [n = 1,512], and Lynx pardinus [n = 197]). We believe that this data set may stimulate the publication of other European countries data sets that would certainly contribute to ecology and conservation‐related research, and therefore assisting on the development of more accurate and tailored conservation management strategies for each species. There are no copyright restrictions; please cite this data paper when the data are used in publications.